FMMSIC: a hybrid fuzzy based decision support system for MMS (in order to estimate interrelationships between criteria)

Abstract

One of the main tasks in exploitation of ore-body is to select a suitable mining method. In mining method selection (MMS) problems, a decision procedure has to choose the best exploitation method that satisfies the evaluation criteria. It is generally hard to find a mining method that meets all the criteria simultaneously, therefore a good compromise solution is preferred as the final selection. Furthermore, the MMS problem is an inherently uncertain activity. To deal with the uncertainty, this paper presents an hybrid decision support system based on the fuzzy multi attribute decision making, named the fuzzy mining method selection with interrelation criteria (FMMSIC). FMMSIC models the relative weights of criteria by combining the fuzzy analytic network process and fuzzy entropy, and discusses using these hybrid techniques to determine the overall weights. Subsequently, the technique for order preference by similarity to an ideal solution method was modified by various normalization norms according to the MMS problem condition. Finally, to illustrate how the FMMSIC is used for the MMS problems, an empirical study of a real case is conducted. It shows by means of an application that the FMMSIC is well suited as a decision support system for the MMS.

Multiple criteria approach in the mining method selection

“…The main deficiency of this paper reflects through neglecting of uncertainty. Some authors, that examined the problem of mining method selection, proposed the application of the extensions of the MCDM methods (Karadogan et al, 2008;Namin, Shahriar, Bascetin, & Ghodsypour, 2012;Dehghani, Siami, & Haghi, 2017;Liang, Zhao, & Hong, 2018). By introducing the fuzzy, grey or neutrosophic numbers, the vagueness of the environment would be acknowledged in the higher degree and the possibility of making a wrong decision would be minimized.…”

Simultaneous Evaluation of Criteria and Alternatives for Mining Method Selection (Case Studies: Gol-E-Gohar No. 3 Iron Ore and Chahar-Gonbad Copper Ore)

“…The mentioned methods have limitations in terms of the number of influential parameters and do not employ a compensatory approach. This means that the strength of one parameter cannot compensate for the weakness of another parameter (Samimi Namin et al, 2012). In the past two decades, the use of multi criteria decision analysis (MCDA) models has become prevalent.…”

Dimensional Analysis under Linguistic Pythagorean Fuzzy Set

“…Most evaluation models ignore the interrelationships between criteria or do not employ methods that examine deeply the interrelationships. They usually assume that criteria are independent, however, they are not always independent of each other [12][13][14][15]. At the same time the values of criteria are generally assessed by experts according to Qin [16].…”

“…At the same time the values of criteria are generally assessed by experts according to Qin [16]. It is often difficult to ensure the absolute objectivity as the MCDM process in real life usually involves vague or imprecise information and the independence of criteria is not mandatory [15].…”

“…To assume that all the input data (criteria) are independent and do not take into consideration the mutual relationship among input data, therefore, few studies are concerned about considering the interrelationship among criteria in MDCM [12][13][14][15]42].…”